Imaging cameras in mail processing machines may capture a distorted image of an address block when the mailpiece is not oriented in an expected manner with the camera. Examples include soft packages, tubes, non-rectangular shapes, etc. This distorted image may cause subsequent optical character recognition (OCR) processes to degrade or fail, resulting in the mailpiece being rejected from the automated sorting system and, hence, requiring manual sorting processes.
By way of more specific explanation, imaging geometry problems due to unusually shaped or situated mailpieces with respect to the imaging camera will result in distorted images. Distorted images generally are not corrected in the image domain but, if possible, are dealt with by a robust OCR system. While this may work for small distortions, larger distortions will exceed the algorithms ability to deal with the problem and the OCR results will be unusable.
For example, in cases when the image is warped, OCR generally may fail by breaking what should be a single line of text into several lines and perhaps even incorrectly grouping small segments of text from different lines together. In cases when the image is sheared, OCR may have difficulty both in segmenting the characters due to the slanted posture and in recognizing the characters. In these cases, the mailpieces cannot be sorted with automated approaches and, instead, the mailpieces will need to be manually sorted resulting in increased costs.